Thermal and Oxidative Degradation of Aqueous N, N-Diethylethanolamine (DEEA) at Stripping Conditions for CO2 Capture
Bibliographic record
Abstract
An exact and reliable estimation of amine degradation, which can lead to significant problems, such as solvent losses, degradation by-products, fouling, foaming, corrosion, and increasing solution viscosity, is very important for development of innovative amines with higher chemical stability. In this study, thermal and oxidative degradations of aqueous N, N- Diethylethanolamine (DEEA) solution with CO 2 were investigated in a 600 mL stainless steel autoclave and compared with aqueous MEA solution. The results showed that DEEA solutions demonstrated a higher resistance to thermal degradation. The influence of key operating parameters, such as temperature, CO 2 loading, and DEEA concentration, on DEEA loss (mol%) were also investigated. In addition, the possible mechanisms of DEEA thermal degradation have been developed on the basis of the identified products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".